To achieve and maintain prosperity, a business is frequently called upon to make decisions concerning where to acquire various goods and services. In the context of manufacturing, raw materials that are to be processed or assembled to manufacture a product must be replaced if additional products are to be manufactured. Similarly, a service business often consumes supplies in the process of delivering services to its customers. These supplies must likewise be replaced if the services are to continue.
Supplies can be tangible goods, for example iron and coke used to make steel, or they can be intangible services, for example collection services for collecting delinquent payments. Throughout this specification, the term “item” is used to refer to both goods and services.
In a conventional method for acquiring items, a buyer opens a reverse auction, hereafter referred to as an auction, by distributing a “request-for-quotation,” or RFQ, to prospective suppliers. The RFQ contains a list of what items the buyer would like to purchase. In some cases, the RFQ contains additional information pertinent to the proposed transaction, such as minimum or maximum quantities, delivery dates or standards of quality. The RFQ can thus be viewed as a collection of constraints imposed by the buyer on a proposed transaction.
In response to the RFQ, the prospective suppliers submit bids, which are essentially offers to enter into a contract with the buyer. These bids typically include offer prices together with additional proposed terms. The response can thus be viewed as a collection of constraints imposed by the supplier on the proposed transaction.
To the extent that the constraints imposed by the buyer and the constraints imposed by a particular supplier are both met, a transaction between the buyer and the particular supplier is feasible. In a typical auction, there will be numerous suppliers for which this is the case. The buyer must then choose which of those suppliers are to be awarded the bid. The optimal combination of suppliers, together with the list of items to be ordered from each supplier, is referred to as an optimal award schedule.
Where price is the buyer's sole concern, and all bids can yield a unit price-per-item, the process of determining an optimal award schedule is decidedly trivial. One simply selects the supplier offering the lowest price-per-item. If the buyer requires additional quantities of that item once that supplier's supply of the item is exhausted, the buyer then selects the supplier having the next lowest price-per-item. This process continues until the buyer's constraint on the quantity of the item has been met.
In reality, however, modern business-to-business transactions are far from being so simple. For example, a supplier's price for an item can be made to depend on the quantity of that item purchased. Or, the supplier may give one price for a bundle of disparate items, in which case it is unclear how to allocate this price among the items.
In addition, other less clearly quantifiable factors must often be considered. For example, the quality of goods or the reputation of the supplier for reliability, or the supplier's solvency, may need to be considered. The buyer may also have internally generated policies, or business rules, that further constrain which the choice of which suppliers can be awarded a bid.
In addition, the relative importance of the various factors can vary depending on the context in which the decision is made. For example, anyone who has been a passenger on a commercial airline might reasonably infer that it is more important for meals be delivered to the aircraft prior to the scheduled departure time than it is that the meals stimulate the palate. Similarly, in purchasing latex gloves for a fast food restaurant, a slight porosity of the glove may not be as important as a low price. In contrast, when purchasing latex gloves for an operating room, the price savings may be irrelevant given the far more serious consequences of contamination.
The complexity of compiling a quantitatively justifiable schedule of optimal awards given all the foregoing constraints is daunting even when the choice is limited to a few suppliers bidding on a limited number of items. As a result, decision-makers often rely on what is euphemistically termed “heuristic reasoning” when awarding bids to suppliers. That decisions of such importance are based on what amounts to educated guesswork is alarming, particularly in an era in which computational tools are so widely available.